NVIDIA Tegra X1 vs Apple M2 Pro (10-CPU 16-GPU)
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CPU comparison with benchmarks
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| NVIDIA Tegra X1 | Apple M2 Pro (10-CPU 16-GPU) | |
CPU comparisonNVIDIA Tegra X1 or Apple M2 Pro (10-CPU 16-GPU) - which processor is faster? In this comparison we look at the differences and analyze which of these two CPUs is better. We compare the technical data and benchmark results.
The NVIDIA Tegra X1 has 8 cores with 8 threads and clocks with a maximum frequency of 2.00 GHz. Up to 8 GB of memory is supported in 2 memory channels. The NVIDIA Tegra X1 was released in Q1/2017. The Apple M2 Pro (10-CPU 16-GPU) has 10 cores with 10 threads and clocks with a maximum frequency of 3.50 GHz. The CPU supports up to 32 GB of memory in 2 memory channels. The Apple M2 Pro (10-CPU 16-GPU) was released in Q1/2023. |
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| NVIDIA Tegra (2) | Family | Apple M series (25) |
| NVIDIA Tegra X1 (2) | CPU group | Apple M2 (8) |
| 2 | Generation | 2 |
| Cortex-A57/-A53 | Architecture | M2 |
| Mobile | Segment | Mobile |
| -- | Predecessor | Apple M1 Pro (10-CPU 14-GPU) |
| -- | Successor | Apple M3 Pro (11-CPU 14-GPU) |
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CPU Cores and Base FrequencyThe NVIDIA Tegra X1 has 8 CPU cores and can calculate 8 threads in parallel. The clock frequency of the NVIDIA Tegra X1 is 2.00 GHz while the Apple M2 Pro (10-CPU 16-GPU) has 10 CPU cores and 10 threads can calculate simultaneously. The clock frequency of the Apple M2 Pro (10-CPU 16-GPU) is at 0.66 GHz (3.50 GHz). |
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| NVIDIA Tegra X1 | Characteristic | Apple M2 Pro (10-CPU 16-GPU) |
| 8 | Cores | 10 |
| 8 | Threads | 10 |
| hybrid (big.LITTLE) | Core architecture | hybrid (big.LITTLE) |
| No | Hyperthreading | No |
| No | Overclocking ? | No |
| 2.00 GHz 4x Cortex-A57 |
A-Core | 0.66 GHz (3.50 GHz) 6x Avalanche |
| 2.00 GHz 4x Cortex-A53 |
B-Core | 0.60 GHz (2.42 GHz) 4x Blizzard |
NPU AI performanceThe performance values of the processor's AI unit. The isolated NPU performance is specified here, the total AI performance (NPU+CPU+iGPU) can be higher. Processors with support for artificial intelligence (AI) and machine learning (ML) can process many calculations, especially audio, image and video processing, much faster than classic processors. |
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| NVIDIA Tegra X1 | Characteristic | Apple M2 Pro (10-CPU 16-GPU) |
| -- | AI hardware | Apple Neural Engine |
| -- | AI specifications | 16 Neural cores @ 15.8 TOPS |
| -- | NPU + CPU + iGPU | -- |
Integrated graphics (iGPU)The NVIDIA Tegra X1 or Apple M2 Pro (10-CPU 16-GPU) has integrated graphics, called iGPU for short. The iGPU uses the system's main memory as graphics memory and sits on the processor's die. |
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| NVIDIA Tegra X1 (Maxwell) | GPU | Apple M2 Pro (16 Core) |
| 0.30 GHz | GPU frequency | 0.45 GHz |
| 1.00 GHz | GPU (Turbo) | 1.40 GHz |
| 1 | GPU Generation | 2 |
| 20 nm | Technology | 5 nm |
| 1 | Max. displays | 3 |
| 2 | Compute units | 256 |
| 256 | Shader | 2048 |
| No | Hardware Raytracing | No |
| No | Frame Generation | No |
| 2 GB | Max. GPU Memory | 32 GB |
| 12 | DirectX Version | -- |
Hardware codec supportA photo or video codec that is accelerated in hardware can greatly accelerate the working speed of a processor and extend the battery life of notebooks or smartphones when playing videos. |
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| NVIDIA Tegra X1 (Maxwell) | GPU | Apple M2 Pro (16 Core) |
| Decode | Codec h265 / HEVC (8 bit) | Decode / Encode |
| Decode | Codec h265 / HEVC (10 bit) | Decode / Encode |
| Decode / Encode | Codec h264 | Decode / Encode |
| Decode | Codec VP9 | Decode / Encode |
| Decode | Codec VP8 | Decode |
| No | Codec AV1 | No |
| Decode | Codec AVC | Decode |
| Decode | Codec VC-1 | Decode |
| Decode / Encode | Codec JPEG | Decode / Encode |
Memory & PCIeThe NVIDIA Tegra X1 can use up to 8 GB of memory in 2 memory channels. The maximum memory bandwidth is 25.6 GB/s. The Apple M2 Pro (10-CPU 16-GPU) supports up to 32 GB of memory in 2 memory channels and achieves a memory bandwidth of up to 102.4 GB/s. |
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| NVIDIA Tegra X1 | Characteristic | Apple M2 Pro (10-CPU 16-GPU) |
| LPDDR4-3200 | Memory | LPDDR5-6400 |
| 8 GB | Max. Memory | 32 GB |
| 2 (Dual Channel) | Memory channels | 2 (Dual Channel) |
| 25.6 GB/s | Max. Bandwidth | 102.4 GB/s |
| No | ECC | No |
| 2.50 MB | L2 Cache | 28.00 MB |
| -- | L3 Cache | -- |
| -- | PCIe version | 4.0 |
| -- | PCIe lanes | -- |
| -- | PCIe Bandwidth | -- |
Thermal ManagementThe thermal design power (TDP for short) of the NVIDIA Tegra X1 is 7 W, while the Apple M2 Pro (10-CPU 16-GPU) has a TDP of 30 W. The TDP specifies the necessary cooling solution that is required to cool the processor sufficiently. |
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| NVIDIA Tegra X1 | Characteristic | Apple M2 Pro (10-CPU 16-GPU) |
| 7 W | TDP (PL1 / PBP) | 30 W |
| -- | TDP (PL2) | -- |
| -- | TDP up | -- |
| 5 W | TDP down | -- |
| -- | Tjunction max. | 100 °C |
Technical detailsThe NVIDIA Tegra X1 is manufactured in 20 nm and has 2.50 MB cache. The Apple M2 Pro (10-CPU 16-GPU) is manufactured in 5 nm and has a 28.00 MB cache. |
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| NVIDIA Tegra X1 | Characteristic | Apple M2 Pro (10-CPU 16-GPU) |
| 20 nm | Technology | 5 nm |
| Chiplet | Chip design | Chiplet |
| Armv8-A (64 bit) | Instruction set (ISA) | Armv8.5-A (64 bit) |
| -- | ISA extensions | Rosetta 2 x86-Emulation |
| -- | Socket | -- |
| None | Virtualization | Apple Virtualization Framework |
| No | AES-NI | Yes |
| Operating systems | macOS, iPadOS | |
| Q1/2017 | Release date | Q1/2023 |
| -- | Release price | -- |
| show more data | show more data | |
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Rate these processors
Average performance in benchmarks
⌀ Single core performance in 1 CPU benchmarks
⌀ Multi core performance in 1 CPU benchmarks
Geekbench 6 (Single-Core)
Geekbench 6 is a benchmark for modern computers, notebooks and smartphones. What is new is an optimized utilization of newer CPU architectures, e.g. based on the big.LITTLE concept and combining CPU cores of different sizes. The single-core benchmark only evaluates the performance of the fastest CPU core, the number of CPU cores in a processor is irrelevant here.
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NVIDIA Tegra X1
8C 8T @ 2.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
10C 10T @ 3.50 GHz |
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Geekbench 6 (Multi-Core)
Geekbench 6 is a benchmark for modern computers, notebooks and smartphones. What is new is an optimized utilization of newer CPU architectures, e.g. based on the big.LITTLE concept and combining CPU cores of different sizes. The multi-core benchmark evaluates the performance of all of the processor's CPU cores. Virtual thread improvements such as AMD SMT or Intel's Hyper-Threading have a positive impact on the benchmark result.
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NVIDIA Tegra X1
8C 8T @ 2.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
10C 10T @ 3.50 GHz |
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iGPU - FP32 Performance (Single-precision GFLOPS)
The theoretical computing performance of the internal graphics unit of the processor with simple accuracy (32 bit) in GFLOPS. GFLOPS indicates how many billion floating point operations the iGPU can perform per second.
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NVIDIA Tegra X1
NVIDIA Tegra X1 (Maxwell) @ 1.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
Apple M2 Pro (16 Core) @ 1.40 GHz |
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Cinebench 2024 (Single-Core)
The Cinebench 2024 benchmark is based on the Redshift rendering engine, which is also used in Maxon's 3D program Cinema 4D. The benchmark runs are each 10 minutes long to test whether the processor is limited by its heat generation.
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NVIDIA Tegra X1
8C 8T @ 2.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
10C 10T @ 3.50 GHz |
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Cinebench 2024 (Multi-Core)
The Multi-Core test of the Cinebench 2024 benchmark uses all cpu cores to render using the Redshift rendering engine, which is also used in Maxons Cinema 4D. The benchmark run is 10 minutes long to test whether the processor is limited by its heat generation.
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NVIDIA Tegra X1
8C 8T @ 2.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
10C 10T @ 3.50 GHz |
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Cinebench R23 (Single-Core)
Cinebench R23 is the successor of Cinebench R20 and is also based on the Cinema 4 Suite. Cinema 4 is a worldwide used software to create 3D forms. The single-core test only uses one CPU core, the amount of cores or hyperthreading ability doesn't count.
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NVIDIA Tegra X1
8C 8T @ 2.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
10C 10T @ 3.50 GHz |
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Cinebench R23 (Multi-Core)
Cinebench R23 is the successor of Cinebench R20 and is also based on the Cinema 4 Suite. Cinema 4 is a worldwide used software to create 3D forms. The multi-core test involves all CPU cores and taks a big advantage of hyperthreading.
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NVIDIA Tegra X1
8C 8T @ 2.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
10C 10T @ 3.50 GHz |
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Geekbench 5, 64bit (Single-Core)
Geekbench 5 is a cross plattform benchmark that heavily uses the systems memory. A fast memory will push the result a lot. The single-core test only uses one CPU core, the amount of cores or hyperthreading ability doesn't count.
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NVIDIA Tegra X1
8C 8T @ 2.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
10C 10T @ 3.50 GHz |
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Geekbench 5, 64bit (Multi-Core)
Geekbench 5 is a cross plattform benchmark that heavily uses the systems memory. A fast memory will push the result a lot. The multi-core test involves all CPU cores and taks a big advantage of hyperthreading.
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NVIDIA Tegra X1
8C 8T @ 2.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
10C 10T @ 3.50 GHz |
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Estimated results for PassMark CPU Mark
Some of the CPUs listed below have been benchmarked by CPU-monkey. However the majority of CPUs have not been tested and the results have been estimated by a CPU-monkey’s secret proprietary formula. As such they do not accurately reflect the actual Passmark CPU mark values and are not endorsed by PassMark Software Pty Ltd.
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NVIDIA Tegra X1
8C 8T @ 2.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
10C 10T @ 3.50 GHz |
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CPU performance per watt (efficiency)
Efficiency of the processor under full load in the Cinebench R23 (multi-core) benchmark. The benchmark result is divided by the average energy required (CPU package power in watts). The higher the value, the more efficient the CPU is under full load.
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NVIDIA Tegra X1
2.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
12,125 CB R23 MC @ 30 W |
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AI performance (NPU)
The performance values of the processor's AI unit. The isolated NPU performance is given here, the total AI performance (NPU+CPU+iGPU) can be higher.
Processors with the support of artificial intelligence (AI) and machine learning (ML) can process many calculations, especially audio, image and video processing, much faster than classic processors. The performance is given in the number (trillions) of arithmetic operations per second (TOPS).
Processors with the support of artificial intelligence (AI) and machine learning (ML) can process many calculations, especially audio, image and video processing, much faster than classic processors. The performance is given in the number (trillions) of arithmetic operations per second (TOPS).
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NVIDIA Tegra X1
8C 8T @ 2.00 GHz |
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Apple M2 Pro (10-CPU 16-GPU)
10C 10T @ 0.66 GHz |
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Devices using this processor |
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| NVIDIA Tegra X1 | Apple M2 Pro (10-CPU 16-GPU) |
| NVIDIA Shield (1. Gen) Nintendo Switch |
Apple MacBook Pro 14 (2023) Apple mac mini (2023) |
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